Materializing architecture for social care: Brick walls and compromises in design for later life

This article reports on an ethnography of architectural projects for later life social care in the UK. Informed by recent debates in material studies and “materialities of care” we offer an analysis of a care home project that is sensitive to architectural materials that are not normally associated with care and well-being. Although the care home design project we focus on in this article was never built, we found that design discussions relating to a curved brick wall and bricks more generally were significant to its architectural “making”. The curved wall and the bricks were used by the architects to encode quality and values of care into their design. This was explicit in the design narrative that was core to a successful tender submitted by a consortium comprising architects, developers, contractors, and a care provider to a local authority who commissioned the care home. However, as the project developed, initial consensus for the design features fractured. Using a materialized analysis, we document the tussles generated by the curved wall and the bricks and argue that mundane building materials can be important to, and yet marginalized within, the relations inherent to an “architectural care assemblage.” During the design process we saw how decisions about materials are contentious and they act as a catalyst of negotiations that compromise “materialities of care.”     

Flight initiation distance changes across landscapes and habitats in a successful urban coloniser

Urban Ecosystems - Urbanisation is a major land use change that introduces novel sources of disturbance and risk into an ecosystem. Successful urban species modify their fear behaviour in response...     

Covenant Attachment: A Constructivist Grounded Theory of Christian Couples and God

The purpose of this constructivist grounded theory study was to develop a deeper understanding of the relational system of married couples and God. We interviewed nine marital couples from Christian denominations that reported having a strong relationship with each other and with God together. We used constructivist grounded theory techniques presented by Charmaz (2006) and analyzed emergent categories of behaviors, emotions, and cognitions to construct a theory and model of Christian marital couples and their shared relationship with God. We then compared and contrasted the results and theory to existing literature on attachment theory and theorized a shared attachment to God. We applied the theological concept of kinship covenant to the results in order to organize and situate the theory into a Christian framework. Finally, we discuss clinical, pastoral, and future research implications.     

Adaptive Shrinkage in Bayesian Vector Autoregressive Models

Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis. For both applications, shrinkage priors can help improving inference. In this article, we apply the Normal-Gamma shrinkage prior to the VAR with stochastic volatility case and derive its relevant conditional posterior distributions. This framework imposes a set of normally distributed priors on the autoregressive coefficients and the covariance parameters of the VAR along with Gamma priors on a set of local and global prior scaling parameters. In a second step, we modify this prior setup by introducing another layer of shrinkage with scaling parameters that push certain regions of the parameter space to zero. Two simulation exercises show that the proposed framework yields more precise estimates of model parameters and impulse response functions. In addition, a forecasting exercise applied to U.S. data shows that this prior performs well relative to other commonly used specifications in terms of point and density predictions. Finally, performing structural inference suggests that responses to monetary policy shocks appear to be reasonable.     

Monte Carlo studies of bootstrap variability in ROC analysis with data dependency

ROC analysis involving two large datasets is an important method for analyzing statistics of interest for decision making of a classifier in many disciplines. And data dependency due to multiple use of the same subjects exists ubiquitously in order to generate more samples because of limited resources. Hence, a two-layer data structure is constructed and the nonparametric two-sample two-layer bootstrap is employed to estimate standard errors of statistics of interest derived from two sets of data, such as a weighted sum of two probabilities. In this article, to reduce the bootstrap variance and ensure the accuracy of computation, Monte Carlo studies of bootstrap variability were carried out to determine the appropriate number of bootstrap replications in ROC analysis with data dependency. It is suggested that with a tolerance 0.02 of the coefficient of variation, 2,000 bootstrap replications be appropriate under such circumstances.     

A randomized controlled trial of the effects of mindfulness practice on doctoral candidate psychological status

Objectives: To examine the impact of guided mindfulness practice on psychological distress and psychological capital (hope, optimism, resilience, and efficacy) in doctoral candidates. Participants: Recruitment of a convenience sample of doctoral candidates occurred in July 2015 and participants were randomly allocated to the control or intervention group (38 and 34 participants completed the trial, respectively). Methods: A single-blinded, randomized controlled trial with intention-to-treat analysis was conducted. The intervention consisted of a daily guided mindfulness practice, using an audio CD. Indicators of psychological distress and psychological capital were measured pre- and post-trial with validated questionnaires. Results: Compared to the control group, the intervention group reported a statistically significantly reduction in depression (p?=?.045) and increased self-efficacy (p?=?.004), hope (p?=?.000), and resilience (p?=?.011). Conclusions: These results highlight the effectiveness of self-administered mindfulness practice on the psychological health of doctoral candidates, and the positive effect on psychological capital is reported as a key finding.     

Strategizing for social change in nonprofit contexts: A typology of communication approaches in public communication campaigns

Public communication campaigns aim to create social change by influencing audiences’ behaviors and thus help nonprofit organizations fulfill their mission. These campaigns, however, often fail to deliver their anticipated impact. Using public relations research as a theoretical lens, this paper's contribution is twofold: first, we develop a typology that classifies the different communication approaches used in public communication campaigns. Based on one of the most prominent public relations theories, the Four Models of Public Relations, we differentiate communication approaches along the dimensions of communication purpose and communication style. Combining these two dimensions in a typology, we identify the following communication approaches: directing, platforming, mobilizing, and involving. We provide numerous real‐life examples of public campaigns for each one. Second, we formulate propositions about these communication approaches’ effectiveness relying on a key concept of public relations research: namely, audience segmentation. Using the transtheoretical model, we show that audiences can be segmented along five “stages of readiness to adopt a promoted behavior.” Conceptualizing behavior change as an iterative, dynamic process that entails stage progresses as well as backdrops, we derive how audiences’ “stage of readiness” relates to the effectiveness of the identified communication approaches.     

Optimal designs for the development of personalized treatment rules

We study the design of multi-armed parallel group clinical trials to estimate personalized treatment rules that identify the best treatment for a given patient with given covariates. Assuming that the outcomes in each treatment arm are given by a homoscedastic linear model, with possibly different variances between treatment arms, and that the trial subjects form a random sample from an unselected overall population, we optimize the (possibly randomized) treatment allocation allowing the allocation rates to depend on the covariates. We find that, for the case of two treatments, the approximately optimal allocation rule does not depend on the value of the covariates but only on the variances of the responses. In contrast, for the case of three treatments or more, the optimal treatment allocation does depend on the values of the covariates as well as the true regression coefficients. The methods are illustrated with a recently published dietary clinical trial.