The Relationship between Therapeutic Alliance and Service User Satisfaction in Mental Health Inpatient Wards and Crisis House Alternatives: A Cross-Sectional Study

Background Poor service user experiences are often reported on mental health inpatient wards. Crisis houses are an alternative, but evidence is limited. This paper investigates therapeutic alliances in acute wards and crisis houses, exploring how far stronger therapeutic alliance may underlie greater client satisfaction in crisis houses. Methods and Findings Mixed methods were used. In the quantitative component, 108 crisis house and 247 acute ward service users responded to measures of satisfaction, therapeutic relationships, informal peer support, recovery and negative events experienced during the admission. Linear regressions were conducted to estimate the association between service setting and measures, and to model the factors associated with satisfaction. Qualitative interviews exploring therapeutic alliances were conducted with service users and staff in each setting and analysed thematically. Results We found that therapeutic alliances, service user satisfaction and informal peer support were greater in crisis houses than on acute wards, whilst self-rated recovery and numbers of negative events were lower. Adjusted multivariable analyses suggest that therapeutic relationships, informal peer support and negative experiences related to staff may be important factors in accounting for greater satisfaction in crisis houses. Qualitative results suggest factors that influence therapeutic alliances include service user perceptions of basic human qualities such as kindness and empathy in staff and, at service level, the extent of loss of liberty and autonomy. Conclusions and Implications We found that service users experience better therapeutic relationships and higher satisfaction in crisis houses compared to acute wards, although we cannot exclude the possibility that differences in service user characteristics contribute to this. This finding provides some support for the expansion of crisis house provision. Further research is needed to investigate why acute ward service users experience a lack of compassion and humanity from ward staff and how this could be changed

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Structural shape optimization using Cartesian grids and automatic h-adaptive mesh projection

[EN] We present a novel approach to 3D structural shape optimization that leans on an Immersed Boundary Method. A boundary tracking strategy based on evaluating the intersections between a fixed Cartesian grid and the evolving geometry sorts elements as internal, external and intersected. The integration procedure used by the NURBS-Enhanced Finite Element Method accurately accounts for the nonconformity between the fixed embedding discretization and the evolving structural shape, avoiding the creation of a boundary-fitted mesh for each design iteration, yielding in very efficient mesh generation process. A Cartesian hierarchical data structure improves the efficiency of the analyzes, allowing for trivial data sharing between similar entities or for an optimal reordering of thematrices for the solution of the system of equations, among other benefits. Shape optimization requires the sufficiently accurate structural analysis of a large number of different designs, presenting the computational cost for each design as a critical issue. The information required to create 3D Cartesian h- adapted mesh for new geometries is projected from previously analyzed geometries using shape sensitivity results. Then, the refinement criterion permits one to directly build h-adapted mesh on the new designs with a specified and controlled error level. Several examples are presented to show how the techniques here proposed considerably improve the computational efficiency of the optimization process.The authors wish to thank the Spanish Ministerio de Economia y Competitividad for the financial support received through the project DPI2013-46317-R and the FPI program (BES-2011-044080), and the Generalitat Valenciana through the project PROMETEO/2016/007.Marco, O.; Ródenas, J.; Albelda Vitoria, J.; Nadal, E.; Tur Valiente, M. (2017). Structural shape optimization using Cartesian grids and automatic h-adaptive mesh projection. Structural and Multidisciplinary Optimization. 1-21. https://doi.org/10.1007/s00158-017-1875-1S121MATLAB version 8.3.0.532 (R2014a) (2014) Documentation. The Mathworks, Inc., Natick, MassachusettsAbel JF, Shephard MS (1979) An algorithm for multipoint constraints in finite element analysis. Int J Numer Methods Eng 14(3):464–467Amestoy P, Davis T, Duff I (1996) An approximate minimum degree ordering algorithm. SIAM J Matrix Anal Appl 17(4):886–905Barth W, Stürzlinger W (1993) Efficient ray tracing for Bezier and B-spline surfaces. Comput Graph 17 (4):423–430Bennett J A, Botkin M E (1985) Structural shape optimization with geometric problem description and adaptive mesh refinement. AIAA J 23(3):459–464Braibant V, Fleury C (1984) Shape optimal design using b-splines. Comput Methods Appl Mech Eng 44 (3):247–267Bugeda G, Oliver J (1993) A general methodology for structural shape optimization problems using automatic adaptive remeshing. Int J Numer Methods Eng 36(18):3161–3185Bugeda G, Ródenas J J, Oñate E (2008) An integration of a low cost adaptive remeshing strategy in the solution of structural shape optimization problems using evolutionary methods. Comput Struct 86(13–14):1563–1578Chang K, Choi K K (1992) A geometry-based parameterization method for shape design of elastic solids. Mech Struct Mach 20(2):215–252Cho S, Ha S H (2009) Isogeometric shape design optimization: exact geometry and enhanced sensitivity. Struct Multidiscip Optim 38(1):53–70Belegundu D, Zhang YMS, Salagame R (1991) The natural approach for shape optimization with mesh distortion control. Tech. rep., Penn State UniversityDavis T A, Gilbert J R, Larimore S, Ng E (2004) An approximate column minimum degree ordering algorithm. ACM Trans Math Softw 30(3):353–376Doctor L J, Torborg J G (1981) Display techniques for octree-encoded objects. IEEE Comput Graph Appl 1(3):29–38Dunning P D, Kim H A, Mullineux G (2011) Investigation and improvement of sensitivity computation using the area-fraction weighted fixed grid FEM and structural optimization. Finite Elem Anal Des 47(8):933–941Düster A, Parvizian J, Yang Z, Rank E (2008) The finite cell method for three-dimensional problems of solid mechanics. Comput Methods Appl Mech Eng 197(45-48):3768–3782Escobar J M, Montenegro R, Rodríguez E, Cascón J M (2014) The meccano method for isogeometric solid modeling and applications. Eng Comput 30(3):331–343Farhat C, Lacour C, Rixen D (1998) Incorporation of linear multipoint constraints in substructure based iterative solvers. Part 1: a numerically scalable algorithm. Int J Numer Methods Eng 43(6):997–1016Fries T P, Omerović S (2016) Higher-order accurate integration of implicit geometries. Int J Numer Methods Eng 106(5):323–371Fuenmayor F J, Oliver J L (1996) Criteria to achieve nearly optimal meshes in the h-adaptive finite element mehod. Int J Numer Methods Eng 39(23):4039–4061Fuenmayor F J, Oliver J L, Ródenas J J (1997) Extension of the Zienkiewicz-Zhu error estimator to shape sensitivity analysis. Int J Numer Methods Eng 40(8):1413–1433García-Ruíz M J, Steven G P (1999) Fixed grid finite elements in elasticity problems. Eng Comput 16 (2):145–164Gill P, Murray W, Saunders M, Wright M (1984) Procedures for optimization problems with a mixture of bounds and general linear constraints. ACM Trans Math Software 10:282–298González-Estrada O A, Nadal E, Ródenas J J, Kerfriden P, Bordas S P A, Fuenmayor F J (2014) Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery. Comput Mech 53(5):957–976Ha S H, Choi K K, Cho S (2010) Numerical method for shape optimization using T-spline based isogeometric method. Struct Multidiscip Optim 42(3):417–428Haftka R T, Grandhi R V (1986) Structural shape optimization: A survey. Comput Methods Appl Mech Eng 57(1):91–106Haslinger J, Jedelsky D (1996) Genetic algorithms and fictitious domain based approaches in shape optimization. Struc Optim 12:257–264Hughes T J R, Cottrell J A, Bazilevs Y (2005) Isogeometric Analysis: CAD, Finite Elements, NURBS, Exact Geometry, and Mesh Refinement. Comput Methods Appl Mech Eng 194:4135–4195Jackins C L, Tanimoto S L (1980) Oct-tree and their use in representing three-dimensional objects. Comput Graphics Image Process 14(3):249–270Kajiya J T (1982) Ray Tracing Parametric Patches. SIGGRAPH Comput Graph 16(3):245–254van Keulen F, Haftka R T, Kim N (2005) Review of options for structural design sensitivity analysis. Part I: linear systems. Comput Methods Appl Mech Eng 194(30-33):3213–3243Kibsgaard S (1992) Sensitivity analysis-the basis for optimization. Int J Numer Methods Eng 34(3):901–932Kikuchi N, Chung K Y, Torigaki T, Taylor J E (1986) Adaptive finite element methods for shape optimization of linearly elastic structures. Comput Methods Appl Mech Eng 57(1):67–89Kim N H, Chang Y (2005) Eulerian shape design sensitivity analysis and optimization with a fixed grid. Comput Methods Appl Mech Eng 194(30–33):3291–3314Kudela L, Zander N, Kollmannsberger S, Rank E (2016) Smart octrees: Accurately integrating discontinuous functions in 3d. Comput Methods Appl Mech Eng 306(1):406–426Kunisch K, Peichl G (1996) Numerical gradients for shape optimization based on embedding domain techniques. Comput Optim 18:95–114Li K, Qian X (2011) Isogeometric analysis and shape optimization via boundary integral. Computer-Aided Design 43(11):1427–1437Lian H, Kerfriden P, Bordas S P A (2016) Implementation of regularized isogeometric boundary element methods for gradient-based shape optimization in two-dimensional linear elasticity. Int J Numer Methods Eng 106 (12):972–1017Liu L, Zhang Y, Hughes T J R, Scott M A, Sederberg T W (2014) Volumetric T-spline Construction using Boolean Operations. Eng Comput 30(4):425–439Marco O, Sevilla R, Zhang Y, Ródenas J J, Tur M (2015) Exact 3D boundary representation in finite element analysis based on Cartesian grids independent of the geometry. Int J Numer Methods Eng 103:445–468Marco O, Ródenas J J, Fuenmayor FJ, Tur M (2017a) An extension of shape sensitivity analysis to an immersed boundary method based on cartesian grids. Computational Mechanics SubmittedMarco O, Ródenas J J, Navarro-Jiménez JM, Tur M (2017b) Robust h-adaptive meshing strategy for arbitrary cad geometries in a cartesian grid framework. Computers & Structures SubmittedMeagher D (1980) Octree Encoding: A New Technique for the Representation, Manipulation and Display of Arbitrary 3-D Objects by Computer. Tech. Rep. IPL-TR-80-11 I, Rensselaer Polytechnic InstituteMoita J S, Infante J, Mota C M, Mota C A (2000) Sensitivity analysis and optimal design of geometrically non-linear laminated plates and shells. Comput Struct 76(1–3):407–420Nadal E (2014) Cartesian Grid FEM (cgFEM): High Performance h-adaptive FE Analysis with Efficient Error Control. Application to Structural Shape Optimization. PhD Thesis. Universitat Politècnica de ValènciaNadal E, Ródenas J J, Albelda J, Tur M, Tarancón J E, Fuenmayor F J (2013) Efficient finite element methodology based on cartesian grids: application to structural shape optimization. Abstr Appl Anal 2013:1–19Najafi A R, Safdari M, Tortorelli D A, Geubelle P H (2015) A gradient-based shape optimization scheme using an interface-enriched generalized FEM. Comput Methods Appl Mech Eng 296:1–17Nguyen V P, Anitescu C, Bordas S P A, Rabczuk T (2015) Isogeometric analysis: An overview and computer implementation aspects. Math Comput Simul 117:89–116Nishita T, Sederberg TW, Kakimoto M (1990) Ray Tracing Trimmed Rational Surface Patches. SIGGRAPH Comput Graph 24(4):337–345Nocedal J, Wright SJ (2006) Numerical optimization, 2nd edn. Springer-Verlag, New YorkPandey P C, Bakshi P (1999) Analytical response sensitivity computation using hybrid finite elements. Comput Struct 71(5):525–534Parvizian J, Düster A, Rank E (2007) Finite Cell Method: h- and p- Extension for Embedded Domain Methods in Solid Mechanics. Comput Mech 41(1):121–133Peskin C S (1977) Numerical Analysis of Blood Flow in the Heart. J Comput Phys 25:220–252Poldneff M J, Rai I S, Arora J S (1993) Implementation of design sensitivity analysis for nonlinear structures. AIAA J 31(11):2137–2142Powell M (1983) Variable metric methods for constrained optimization. In: Bachem A, Grotschel M, Korte B (eds) Mathematical Programming: The State of the Art, Springer, Berlin, Heidelberg, pp 288–311Qian X (2010) Full analytical sensitivities in NURBS based isogeometric shape optimization. Comput Methods Appl Mech Eng 199(29–32):2059–2071Riehl S, Steinmann P (2014) An integrated approach to shape optimization and mesh adaptivity based on material residual forces. Comput Methods Appl Mech Eng 278:640–663Riehl S, Steinmann P (2016) On structural shape optimization using an embedding domain discretization technique. Int J Numer Methods Eng 109(9):1315–1343Ródenas J J, Tarancón J E, Albelda J, Roda A, Fuenmayor F J (2005) Hierarchical Properties in Elements Obtained by Subdivision: a Hierarquical h-adaptivity Program. In: Díez P, Wiberg N E (eds) Adaptive Modeling and Simulation, p 2005Ródenas J J, Corral C, Albelda J, Mas J, Adam C (2007a) Nested domain decomposition direct and iterative solvers based on a hierarchical h-adaptive finite element code. In: Runesson K, Díez P (eds) Adaptive Modeling and Simulation 2007, Internacional Center for Numerical Methods in Engineering (CIMNE), pp 206–209Ródenas J J, Tur M, Fuenmayor F J, Vercher A (2007b) Improvement of the superconvergent patch recovery technique by the use of constraint equations: the SPR-C technique. Int J Numer Methods Eng 70(6):705–727Ródenas J J, Bugeda G, Albelda J, Oñate E (2011) On the need for the use of error-controlled finite element analyses in structural shape optimization processes. Int J Numer Methods Eng 87(11):1105–1126Schillinger D, Ruess M (2015) The finite cell method: A review in the context of higher-order structural analysis of cad and image-based geometric models. Arch Comput Meth Eng 22(3):391– 455Sevilla R, Fernández-Méndez S, Huerta A (2011a) 3D-NURBS-enhanced Finite Element Method (NEFEM). Int J Numer Methods Eng 88(2):103–125Sevilla R, Fernández-Méndez S, Huerta A (2011b) Comparison of High-order Curved Finite Elements. Int J Numer Methods Eng 87(8):719–734Sevilla R, Fernández-Méndez S, Huerta A (2011c) NURBS-enhanced Finite Element Method (NEFEM): A Seamless Bridge Between CAD and FEM. Arch Comput Meth Eng 18(4):441–484Sweeney M, Bartels R (1986) Ray tracing free-form b-spline surfaces. IEEE Comput Graph Appl 6(2):41–49Toth D L (1985) On Ray Tracing Parametric Surfaces. SIGGRAPH Comput Graph 19(3):171–179Tur M, Albelda J, Nadal E, Ródenas J J (2014) Imposing dirichlet boundary conditions in hierarchical cartesian meshes by means of stabilized lagrange multipliers. Int J Numer Methods Eng 98(6):399–417Tur M, Albelda J, Marco O, Ródenas J J (2015) Stabilized Method to Impose Dirichlet Boundary Conditions using a Smooth Stress Field. Comput Methods Appl Mech Eng 296:352–375Yao T, Choi KK (1989) 3-d shape optimal design and automatic finite element regridding. Int J Numer Methods Eng 28(2):369–384Zhang L, Gerstenberger A, Wang X, Liu W K (2004) Immersed Finite Element Method. Comput Methods Appl Mech Eng 293(21):2051–2067Zhang Y, Wang W, Hughes T J R (2013) Conformal Solid T-spline Construction from Boundary T-spline Representations. Comput Mech 6(51):1051–1059Zienkiewicz O C, Zhu J Z (1987) A Simple Error Estimator and Adaptive Procedure for Practical Engineering Analysis. Int J Numer Methods Eng 24(2):337–35

Developing Global Maps of the Dominant Anopheles Vectors of Human Malaria

Simon Hay and colleagues describe how the Malaria Atlas Project has collated anopheline occurrence data to map the geographic distributions of the dominant mosquito vectors of human malaria

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed.</p> <p>Results</p> <p>Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented.</p> <p>Conclusions</p> <p>This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps.</p

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field